RapidUn uses influence estimation to drive adaptive parameter reweighting for efficient LLM unlearning, outperforming baselines with up to 100x efficiency gains on tested models.
Huawei Lin, Jikai Long, Zhaozhuo Xu, and Weijie Zhao
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RapidUn: Influence-Driven Parameter Reweighting for Efficient Large Language Model Unlearning
RapidUn uses influence estimation to drive adaptive parameter reweighting for efficient LLM unlearning, outperforming baselines with up to 100x efficiency gains on tested models.